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16 - Neural Architectures for Natural Language Processing Applications

Published online by Cambridge University Press:  01 February 2024

Mihai Surdeanu
Affiliation:
University of Arizona
Marco Antonio Valenzuela-Escárcega
Affiliation:
University of Arizona
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Summary

In this chapter, we describe several common applications (including the ones we touched on before) and multiple possible neural approaches for each. We focus on simple neural approaches that work well and should be familiar to anybody beginning research in natural language processing or interested in deploying robust strategies in industry. In particular, we describe the implementation of the following applications: text classification, part-of-speech tagging, named entity recognition, syntactic dependency parsing, relation extraction, question answering, and machine translation.

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Deep Learning for Natural Language Processing
A Gentle Introduction
, pp. 246 - 271
Publisher: Cambridge University Press
Print publication year: 2024

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